Edmund K. Turner

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Discrete choice methods model a decision-maker's choice among a set of mutually exclusive and collectively exhaustive alternatives. They are used in a variety of disciplines (transportation, economics, psychology, public policy, etc.) in order to inform policy and marketing decisions and to better understand and test hypotheses of behavior. This(More)
Advances in Intelligent Transportation Systems (ITS) have resulted in the deployment of surveillance systems that automatically collect and store extensive network-wide traffic data. Dynamic Traffic Assignment (DTA) models have also been developed for a variety of dynamic traffic management applications. Such models are designed to estimate and predict the(More)
A stochastic time-dependent (STD) network is defined by treating all link travel times at all time periods as random variables, with possible time-wise and link-wise stochastic dependency. A routing policy is a decision rule which specifies what node to take next out of the current node based on the current time and online information. A formal framework is(More)
Dynamic congestion pricing is an approach to control the traffic flow on the network by setting variable tolls that are adjusted with time based on the traffic condition. Different models have been developed and tested in the past. However, most of these models are based on deterministic network equilibrium rather than stochastic choices of travelers, and(More)
Drivers using information from an Advanced Traveler Information System (ATIS) could potentially make better travel decisions to reduce travel time and increase trip reliability, thereby benefiting both guided drivers as well as those without such access. However, market penetration of ATIS can have dramatic effects on the performance of the transportation(More)
In this thesis we study online optimization problems in routing and scheduling. An online problem is one where the problem instance is revealed incrementally. Decisions can (and sometimes must) be made before all information is available. We design and analyze (polynomial-time) online algorithms for a variety of problems. We utilize worst-case competitive(More)
We present a practical method for estimating the probability distribution of a travel demand forecast. Given a forecast of any variable of interest, such as revenue or ridership, the approach identifies independent sources of uncertainty, estimates a probability distribution of each source, estimates the sensitivity of the variable to each source, and then(More)
There is a long history of projects and regulations that have had limited or even counterproductive results. These unforeseen effects are due to the failure of planners to capture all of the complexity inherent in urban dynamics. With the increasing risks of global warming, policymakers and planners need to make optimal or close-to-optimal decisions on how(More)